(1) Field of the Invention
The present invention generally relates to a code set including codes for describing a binary-valued image such as a character or a figure, and a method and system for describing an image using the code set.
(2) Description of the Related Art
Nowadays, there have been proposed various image description methods for describing images to store images in computers. The proposed image description methods are based on the types of images to be described and applied fields. For example, there are known, as methods for describing binary-valued images, a topological description method, a parameter description method and a chain-code description method. The topological description method is a rough description method which pays attention to the number of concatenation components of an image pattern and the number of holes in an image pattern. The parameter description method is capable of describing an image pattern in detail and completely preserving the shape of the contour of the image pattern. The chain-code description method is a practical method.
Further, a quasi-topological description method, a vertical topological description method (in Japanese Patent Application No.3-253186), and a sedin-code description method have been proposed. These methods are categorized between the rough description methods and the precise description methods. Due to the above description methods, it becomes to simplify algorithms for compressing and recognizing image data.
Normally, images includes various noises (e.g. shading off and break in lines). Hence, these noises must be eliminated from the images before a process for recognizing the image patterns. The following two types of noise cancelling methods are known.
The first type of noise cancelling methods is a filtering process in which pixel data is processed. The second type of noise cancelling methods is a process for eliminating noises after image data is summarized. Normally, the second type of noise cancelling methods is superior to the first type thereof in terms of the quality of computation, the operation speed and intelligence of the noise cancelling process itself. The second type of noise cancelling methods is suitable for the above mentioned vertical topological description method and the sedin code description method.
Further, there is a close relationship between the details of description and noise tolerance of the description. The topological description method is too rough to apply it to the character recognition. The parameter description method and the chain-code description method are too precise to apply these methods to the character recognition. Hence, a dictionary having a very large storage capacity and a very large amount of data processing are needed. Further, these method are liable to be affected by noises.